In vivo detection of carnosine and its derivatives using chemical exchange saturation transfer.

PURPOSE: To detect carnosine, anserine and homocarnosine in vivo with chemical exchange saturation transfer (CEST) at 17.2 T. METHODS: CEST MR acquisitions were performed using a CEST-linescan sequence developed in-house and optimized for carnosine detection. In vivo CEST data were collected from three different regions of interest (the lower leg muscle, the olfactory bulb and the neocortex) of eight rats. RESULTS: The CEST effect for carnosine, anserine and homocarnosine was characterized in phantoms, demonstrating the possibility to separate individual contributions by employing high spectral resolution (0.005 ppm) and low CEST saturation power (0.15 µ$$ \mu $$ T). The CEST signature of these peptides was evidenced, in vivo, in the rat brain and skeletal muscle. The presence of carnosine and anserine in the muscle was corroborated by in vivo localized spectroscopy (MRS). However, the sensitivity of MRS was insufficient for carnosine and homocarnosine detection in the brain. The absolute amounts of carnosine and derivatives in the investigated tissues were determined by liquid chromatography-electrospray ionization-tandem mass spectrometry using isotopic dilution standard methods and were in agreement with the CEST results. CONCLUSION: The robustness of the CEST-linescan approach and the favorable conditions for CEST at ultra-high magnetic field allowed the in vivo CEST MR detection of carnosine and related peptides. This approach could be useful to investigate noninvasively the (patho)-physiological roles of these molecules.

PEAKIT: A Gaussian Process regression analysis tool for chemical exchange saturation transfer spectra.

Chemical Exchange Saturation Transfer (CEST) is a powerful technique for metabolic imaging, capable of exploring concentrations in the µM to mM range. However, extracting quantitative information from Z-spectra can be challenging due to the non-CEST contributions present and the limited knowledge about the exchanging pools. The PEAKIT tool is proposed as an alternative approach to quantifying CEST peaks, which requires no prior assumptions about the frequency offset or the underlying shape of the baseline. Specifically, the tool takes as input an experimental Z-spectrum and proceeds to identify peak candidates. After a baseline estimation based on Gaussian Process regression, PEAKIT outputs the chemical shift offsets, the areas, the heights and the statistical significance of the detected peaks. The performance and limitations of the PEAKIT tool are discussed for in vitro and in vivo applications.